Update config.json #82
Open
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Worked with Alondra Guzman from Quantum Metric to update the integration in their docs. The original integration used a getDecisionObject call to get some values to pass into the QM integration. They were not aware of the availablity of standard variables in the integration, there was no need to grab the decision object. Further, the decision object is different when returning an experiment than when a personalization. There was no check for this and it was causing an error in certain scenarios.
|
|
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Worked with Alondra Guzman from Quantum Metric to update the integration in their docs.
The original integration used a getDecisionObject call to get some values to pass into the QM integration.
They were not aware of the availablity of standard variables in the integration, there was no need to grab the decision object.
Further, the decision object is different when returning an experiment than when a personalization. There was no check for this and it was causing an error in certain scenarios.